Marketplace Lending,
Financial Analysis, and
the Future of Credit


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Marketplace Lending,
Financial Analysis, and
the Future of Credit
Integration, Profitability and
Risk Management

IOANNIS AKKIZIDIS
MANUEL STAGARS


This edition first published 2016
© 2016 Ioannis Akkizidis and Manuel Stagars
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To the innovators shaping the future of credit



Contents

Preface

xvii

Acknowledgments


xix

About the Authors

xxi

About the Website

xxiii

Introduction
I.1 Who is This Book For?
I.2 What is FinTech?
I.2.1 Distinction between Financial Technology Innovation and
Financial Innovation
I.3 Why Does This Book Focus on Online Lending?
I.4 The Hybrid Financial Sector: The Opportunity to Build a Healthier
Financial System

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PART ONE

FinTech and the Online Lending Landscape—Where Are We Now?
CHAPTER 1

Introduction to the Business Models in Financial Technology
1.1

Innovation Themes in FinTech
1.1.1 Online lending
1.1.2 Crowdfunding and crowdinvesting
1.1.3 Transactions and payments
1.1.4 Personal Financial Management
1.1.5 Digital currency and cryptocurrency
1.1.6 Mobile point of sale (mPOS)
1.1.7 Online financial advisory
1.1.8 Mobile-first banks
1.1.9 A dynamic and fragmented space

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1.2

The Promises and Pitfalls of FinTech Business Models
1.2.1 Streamlining the user experience (UX) and digital integration
1.2.2 Setting an industry standard that the financial industry failed to get
off the ground
1.2.3 Using someone else’s network while only paying marginal cost
1.2.4 Providing a worse service to customers at a lower price
1.3 The Pitfalls
1.3.1 Overestimating the ability of data science to deal with concentration
and adverse selection
1.3.2 Overestimating the value of Big Data in transactions
1.3.3 Overestimating people’s willingness to trust a FinTech company
instead of another middleman
1.3.4 Overestimating the regulators’ willingness to pardon a FinTech
company flouting the rules
1.4 Why is Financial Technology Innovation Important?
1.5 Challenges and Roadblocks for FinTech Companies
1.5.1 Lack of a human interface
1.5.2 The need for banking licenses
1.5.3 Concerns over privacy
1.6 FinTech is a Long-Term Play
1.7 Concluding Remarks

CHAPTER 2
How Does Online Lending Work? An Overview with a Focus on Marketplace Lending

2.1 Reliance on Technology and Data
2.2 How Do Online Lenders Differ From Banks?
2.3 Types of Online Lenders
2.3.1 Marketplace lending platforms
2.3.2 Online balance sheet lenders
2.3.3 Lender-agnostic marketplaces
2.4 Some Background on Peer-to-Peer Networks
2.4.1 Disintermediation or re-intermediation?
2.4.2 Infomediaries, intermediary-oriented marketplaces, and the
information value chain
2.5 The Business Model of Marketplace Lending Platforms
2.6 Onboarding Process
2.6.1 Borrower onboarding
2.6.2 Lender onboarding
2.7 Comparing Marketplace Loans with Bank Credit or Credit Card Debt
2.7.1 How do marketplace loans differ from bank credit?
2.7.2 How do marketplace loans differ from credit cards?
2.8 Who Are the Alternative Borrowers?
2.9 Who Are Investors in Marketplace Loans?
2.10 Underwriting and Credit Scoring
2.11 Regulation
2.11.1 Transparency and disclosure
2.11.2 Standardization of oversight and monitoring

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2.12
2.13

The Response of Banks to Online Lending
Concluding Remarks

CHAPTER 3
What Made the Rise of Online Lending Possible?
3.1 Technological Factors
3.1.1 Cheap and ubiquitous computing power, coupled with a revolution
in Big Data and analytics
3.1.2 Faster technology adoption
3.1.3 Internet proliferation and network effects
3.1.4 The boom in mobile screens
3.2 Social Factors
3.2.1 Digital connectedness and friendships
3.2.2 Impatience with the know-your-customer process
3.2.3 Sentiment against the established financial sector
3.3 Structural Factors

3.3.1 Stricter banking regulation
3.3.2 Disappearance of smaller banks has decreased access to credit for
consumers and SMEs
3.3.3 Low interest rate environment
3.4 The Perfect Storm
3.4.1 From unbundling to fragmentation and back
3.5 A Divergence of Trends
3.6 Concluding Remarks

CHAPTER 4
Why FinTech Lives Outside of Banks
4.1 The Technology Mudslide Hypothesis: Sustaining Innovation vs.
Disruptive Innovation
4.1.1 Small unproven markets with low-margin products
4.1.2 The need for discovery-driven planning
4.2 Will Banks Notice the Next FinTech Breakthrough?
4.2.1 Incentive misalignment between the short term and the long term
4.2.2 Forcing banks to collaborate with online lenders
4.2.3 Innovating in-house vs. buying innovation
4.3 Why Do Banks Have Difficulty in Innovating?
4.3.1 Underinvestment in core competencies
4.3.2 Imprisoned resources
4.3.3 Bounded innovation
4.3.4 Performers vs. producers
4.3.5 Divergence between core competencies of banks with customer
needs
4.4 Developing Core Competence in Financial Technology Innovation
4.4.1 The trap of marginal thinking
4.4.2 The way forward
4.5 Concluding Remarks


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PART TWO

The Status Quo of Analytics in the Financial Industry—The Perspective of
Banks

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P2.1
P2.2
P2.3
P2.4
P2.5


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Banking is Innovation
Banking Goes Mobile
Banks Are Far From Dead
How to Read This Part of the Book
What We Discuss in This Part

CHAPTER 5
Financial Contracts
5.1 Contract Elements
5.2 Time in Financial Contracts
5.3 Contract Mechanisms Producing Financial Events
5.3.1 Principal patterns
5.3.2 Interest patterns
5.3.3 Accrual interest patterns
5.3.4 Credit enhancements patterns
5.3.5 Behavior patterns
5.3.6 Other patterns
5.3.7 Example of financial events
5.4 Concluding Remarks

CHAPTER 6
Markets
6.1 Real-world and Risk-neutral Expectations of Markets
6.2 Economic Scenarios Based on Real-world Probabilities

6.3 The Risk-neutral Expectations
6.3.1 Yield curves
6.3.2 Forward rates and prices
6.4 Beyond Market Risk-Free Rates
6.4.1 Credit discount spreads based on risk-neutral default probabilities
6.4.2 Liquidity spreads
6.5 Discounting Cash Flows
6.6 Considering Market Elements in P2P Finance
6.7 Concluding Remarks

CHAPTER 7
Counterparties
7.1 Types and Roles of Counterparties
7.2 Descriptive Characteristics
7.3 Default Probability
7.3.1 Structural models
7.3.2 Intensity models
7.3.3 Real-world and risk-neutral default probabilities
7.4 Credit Ratings

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7.5 Credit Spreads Based on Real-world Probabilities
7.6 Link of Counterparties via Markets
7.6.1 Allocating obligor to its own specific risk
7.6.2 Allocating obligor to specific market
7.6.3 Apportioning obligors across several markets
7.6.4 Allocating several obligors to a single market
7.6.5 Allocating obligors to several correlated markets
7.7 Concluding Remarks

CHAPTER 8
Behavior Risk
8.1
8.2
8.3
8.4
8.5
8.6
8.7
8.8

Prepayments
Draw-downs/Remaining Principal/Facilities and Credit Lines
Withdrawals
Selling
Default and Downgrading
Use at Default
Recoveries
Concluding Remarks

CHAPTER 9

Credit Exposures
9.1
9.2
9.3
9.4
9.5
9.6
9.7

Gross Exposure
Net Exposure
Evolution of the Gross and Net Exposures
Exposure Distribution
Credit Losses
Link of Counterparties via Credit Exposures
Concluding Remarks

CHAPTER 10
Credit Enhancements
10.1
10.2

10.3

10.4

What Are Credit Enhancements? Types and Structure
Asset-based Credit Enhancements
10.2.1 Allocating collateral to credit exposures
10.2.2 Valuing and adjusting asset-based credit enhancements

Counterparty-based Credit Enhancements
10.3.1 Guarantees
10.3.2 Allocating guarantees to credit exposures
10.3.3 Credit derivatives
10.3.4 Lack of credit enhancements in marketplace lending exposures
Additional Elements Considered in Credit Enhancements
10.4.1 Double default
10.4.2 Wrong way risk
10.4.3 Maturity mismatch and payment times
10.4.4 Contracts and counterparties dependencies via credit
enhancements

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10.5

10.6

Extending Credit Enhancements in Marketplace Lending
10.5.1 Real estate titles
10.5.2 Phone contracts as stores of value
10.5.3 Loyalty points
10.5.4 Life insurance
10.5.5 Guarantor systems
Concluding Remarks

CHAPTER 11
Systemic and Concentration Risks
11.1

11.2
11.3
11.4
11.5
11.6
11.7

Credit Exposure Systemic Risk
11.1.1 Chain reactions after default credit event
11.1.2 Chain reactions after credit downgrading
Counterparty Systemic Risk
Systemic Risk Exposures and Losses
Credit Exposure Concentration Risk

Counterparty Concentration Risk
Systemic Risk and Portfolio Diversification
Concluding Remarks

CHAPTER 12
Liquidity, Value, Income, Risk and New Production
12.1

Liquidity
12.1.1 Financial contracts and liquidity
12.1.2 The time factor and types of analysis in liquidity
12.1.3 Market and funding liquidity risks
12.1.4 Measuring and reporting liquidity and risk
12.2 Value and Income
12.2.1 Estimating value
12.2.2 Estimating income
12.2.3 Profit and loss
12.2.4 Valuation principles
12.2.5 Risk on value and income
12.2.6 Stress testing
12.2.7 Designing dynamic and integrated stress testing
12.2.8 Stochastic process
12.2.9 Economic capital allocation and risk adjustments
12.2.10 Some key points in applying risk management
12.3 New Production
12.4 Treasury and Funds Transfer Pricing (FTP)
12.4.1 Funds transfer pricing (FTP) and transfer rates
12.4.2 Treasury in P2P finance
12.5 Concluding Remarks


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Contents

PART THREE

Toward the Future of the Hybrid Financial Sector

215

P3.1 Dangers of a Big Bang Approach to Catch Up with Technology Innovation
P3.2 The Need to Collaborate in a Hybrid Financial System

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CHAPTER 13

Profitability and Risk of Marketplace Loans
13.1

Underlying Assumptions of the Analysis
13.1.1 Getting the input data
13.1.2 Time
13.1.3 Risk factors
13.1.4 Mapping the financial contract
13.1.5 Calculating contractual financial events
13.1.6 Constructing portfolios
13.1.7 Analysis outputs
13.2 Risk Factors
13.2.1 Market risk
13.2.2 Counterparty credit risk
13.2.3 Behavior
13.3 Portfolio Construction
13.3.1 Portfolio exposure
13.4 Modeling Portfolio Performance
13.4.1 Income performance
13.4.2 Liquidity performance
13.4.3 Stress testing
13.4.4 Stress test scenarios
13.5 Risk Management
13.5.1 Operational risk
13.5.2 Likely overestimation of borrower quality in marketplace lending
13.5.3 A note on portfolio restructuring and optimization
13.5.4 A note on collateral and hedging exposure
13.6 The Road Forward
13.7 Concluding Remarks


CHAPTER 14
Digital Competencies and Digital Dilemmas
14.1
14.2

14.3

Digital Competencies
14.1.1 Banks lag in some areas and lead in others: Analytics
Digital Dilemmas
14.2.1 Dilemma 1: Disrupt or defend?
14.2.2 Dilemma 2: Cooperate or compete?
14.2.3 Dilemma 3: Diversify or concentrate?
14.2.4 Dilemma 4: Keep digital businesses separate or integrate them?
14.2.5 Dilemma 5: Buy or sell businesses in the portfolio?
Concluding Remarks

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CHAPTER 15
Digital Strategy
15.1
15.2

15.3
15.4

15.5
15.6
15.7
15.8

Who Needs Digital Strategy?
Frameworks to Analyze the Impact of Innovation
15.2.1 The diffusion of innovations
15.2.2 The hype cycle
15.2.3 Big Bang Disruption
Spotting Signs of Trouble on the Horizon
How Banks Can Overcome the Innovator’s Dilemma
15.4.1 Develop disruptive innovation in a separate company
15.4.2 Plan to fail cheaply
15.4.3 Let those in charge of innovation formulate their own rules and
processes
15.4.4 Find new markets
From Producer to Supplier and Moving to a New Singularity
From Closed Innovation to Open Services Innovation
The Role of Leadership in Driving Emergent Strategy
Concluding Remarks


CHAPTER 16
The Hybrid Financial Sector
16.1

16.2
16.3

16.4
16.5

Forces of Competition in the Digital Age
16.1.1 New pressure on prices and margins
16.1.2 Competitors emerging from unexpected places
16.1.3 Winner-takes-all dynamics
16.1.4 Plug-and-play business models
16.1.5 Growing talent mismatches
16.1.6 Converging global supply and demands
16.1.7 Relentlessly evolving business models—at higher velocity
The Dangers of Knife Fights
Good Ideas in Marketplace Lending That Might Be Here to Stay
16.3.1 Credit scoring with fringe alternative data
16.3.2 Responsive, always-on banking and near-real-time credit
16.3.3 Lending as a Service (LaaS)
16.3.4 The ability to invest in fragments of loans
16.3.5 Unbundled, streamlined financial services
16.3.6 High standards for data and transparency
The Alternative to the Hybrid Financial Sector: A Doomsday Scenario for
Established Banks?
Concluding Remarks


CHAPTER 17
Unified Analytics
17.1

Why Do Marketplace Lending Platforms Need Unified Financial Analytics?
17.1.1 Advantages for lenders
17.1.2 Advantages for borrowers
17.1.3 Advantages for marketplace lending platforms

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17.1.4 Advantages for guarantors and protection sellers
17.1.5 Advantages for banks
17.2 An Overview of a Unified Analytics Platform
17.2.1 Standardizing financial data and analytics

17.3 Concluding Remarks

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Bibliography

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Index

307



Preface

I

n the aftermath of the financial crisis 2007/8, it seemed that the current banking model had
failed. After supporting an unprecedented boom in financial markets for the last couple of
hundred years, the traditional credit sector was now out of sync with the demands of customers.
The system was ripe for a makeover, and online lending promised to step up to the plate. It
was then that we began to think about the potential of FinTech, and marketplace lending
in particular, ushering in the next era of banking. At that time, many marketplace lending

platforms already existed and extended credit to borrowers whom banks turned down. We
saw two additional needs in the market: resilience of marketplace loans so that online lending
platforms could withstand a replay of the financial crisis of 2007/8, and empowerment of small
communities to set up their own marketplace lending platforms with the ease of installing the
blogging platform WordPress.
While one of us has a strong background in financial risk and profitability analysis
(Akkizidis) and the other is an economist who founded several startups (Stagars), it seemed
natural to join forces and take a magnifying glass to the brave new FinTech sector that was
just emerging at the time. We analyzed the scene in much detail, with a focus on marketplace
lending, by exploring its lending business model both structurally and analytically. Would
FinTech introduce innovation in the established processes of credit underwriting? How could
we apply risk and profitability analysis using financial analytics to the emerging asset class of
marketplace loans?
Because we are in close contact with the financial sector that FinTech is trying to disrupt,
drawing parallels between the two was a given. It became clear that both sides have much to
learn from each other. FinTech companies have yet to catch up with the vast experience of
banks in underwriting and managing credit. After a long hard look at the way banks cope with
the emerging threat, it seems the financial sector might be in for a rude awakening unless they
ramp up their capability to innovate in parallel with FinTech entrepreneurs. What can both
sides do in this situation? In the quest to find answers to this question, this book came about.
Thank you for reading it.
In the course of writing, we conducted many interviews with innovators in marketplace
lending and those in charge of innovation in banks. Under our eyes, the peer-to-peer lending
sector rebranded itself as marketplace lending. We watched the online credit sector mushroom
into a multi-billion dollar behemoth with a confidence that would make the most brazen
Wall Street honcho blush. At the same time, banks announced partnerships with marketplace
lending platforms, institutional investors piled into the asset class, and the odd acquisition of
a FinTech startup by a financial institution took place. The structural gap between the new
entrant and the incumbent narrowed, but the alliance between the two is still uneasy and at
risk of disintegrating should there be any economic turmoil ahead.


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MARKETPLACE LENDING, FINANCIAL ANALYSIS, AND THE FUTURE OF CREDIT

Marketplace lenders and banks can do better than that.
There exist clear benefits when the two join forces and evolve the future of credit together.
The future is hardly an either/or proposition, and both parties have complementary roles in
the emerging hybrid financial sector. No single tech company is likely to dominate, just as no
conglomerate of banks will squash all marketplace lenders and prevail as the ringleader. The
future of credit is hybrid, but how to get there is far from obvious. In this book, we have had
much fun examining ways for innovators in marketplace lending and banks to co-create the
future of credit together. When they succeed, the result is a stronger financial sector, one that
is more transparent and more resilient.
Ioannis Akkizidis and Manuel Stagars
Zurich and Singapore


Acknowledgments

W

e are grateful to the FinTech entrepreneurs, financial professionals, and opinion leaders who have tested, challenged, and shaped the ideas in this book. Their stories and
experience have helped us improve our analysis and recommendations. Special thanks to (in
alphabetical order): Arjan Schuette, Brendan Dickinson, Brett King, Dan Ciporin, David Moss,
David Snitkof, Dominic Chang, Frank Rotman, Gregg Schoenberg, Izabella Kaminska, Jon
Moulton, Juerg Mueller, Matt Burton, Michael Chaille, Olivier Berthier, Patrick Goh, and Zoe

Zhang. We appreciate you taking the time and giving us insights into your thinking regarding
the future of credit.
We would also like to thank Vivianne Bouchereau for her outstanding review and corrections through the writing process of this manuscript. Ioannis would also like to thank his
young son Filippos for his amazing smiles given during the dedicated work of writing this
book.
At Wiley, an excellent team turned our ideas into the book you are reading. We would like
to thank Werner Coetzee for believing in this project early on and the entire editorial board for
supporting it. Many thanks to Jeremy Chia for contributing his knowledge and energy towards
the development of this book.

xix



About the Authors

I

oannis Akkizidis, BEng, MSc, PhD (Zurich, Switzerland) is the global product manager
on financial risk management systems, in Wolters Kluwer Financial & Compliance Services,
in Z¨urich, Switzerland. He has experience in designing and implementing advanced solutions
in risk-management and profitability analysis fields for the financial industry all around the
world. Turning theory into practice, he has been involved in many projects for implementing
financial systems and models in the financial industry. Dr Akkizidis wrote his PhD thesis
in modelling non-linear systems at the University of Wales, UK. He is a visiting Lecturer
at the University of Z¨urich on the Master’s Degree program Quantitative Finance, lecturing
on a module based on the book Unified Financial Analysis, the Missing Links of Finance,
published by Wiley, 2009, where he is the co-author. Dr Akkizidis is the author of several
books, book chapters, handbooks and articles, in financial analysis and risk management. He
is also a member of the Steering Committee of the Swiss Risk Association.

Manuel Stagars, CFA, CAIA, ERP (Zurich, Switzerland) is an economist and senior
researcher at Singapore-ETH Centre with a focus on the technological and institutional aspects
of data. He is also a serial entrepreneur who has founded companies in Switzerland, the United
States, and Japan. Mr. Stagars has been supporting startups as an angel investor since 2007
and is a consultant to clients on entrepreneurship, business models and financial strategy. He is
also the author of the books Impact Investment Funds for Frontier Markets in Southeast Asia
(Palgrave Macmillan, 2015), and University Startups and Spin-offs: Guide for Entrepreneurs
in Academia (Apress, 2014).

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About the Website

P

lease visit this book’s companion website at www.wiley.com/go/akkizidis to access the
Annexes and Matlab Model.
The password for downloading the files is: credit123
The files available on the website are:
Annex A: Element of Time in Financial Events
This annex provides the list of the financial events in regards to:
Their appearance at Point in Time (PIT) and Through the Cycle (TTC) iterations.
The type of cash flow defined as Principal, Interest, Dividend, Recovery and Trading
payments.
The resetting process at different times and cash flow types.
These are aligned to the event patterns explained in Section 5.3 of Chapter 5 (Contract
Mechanisms Producing Financial Mechanisms).
Annex B: Reduced Form Models Applied in Marketplace Lending Credit Portfolios

This annex provides a description of the intensity based credit risk models for estimating
the default probability and the arrival time of the credit event. Such an intensity based
model is applied for estimating and stressing, over time, the conditional default probabilities and default times for the marketplace lending portfolios. This model is fully explained
and used in the case study described in Chapter 13 of this book.
Matlab Model
The provided Matlab model considers the information referring to market data, counterparty characteristics and behavior assumptions, mapping the standard contractual bilateral
loan agreements between lenders and borrowers, calculating all expected and unexpected
financial events, and reporting the liquidity, value and income together with their corresponding risk measurements. Stress scenarios, defined by the user, can also be applied
in the credit portfolios. This model is used for performing the financial analysis of existing marketplace loans, as discussed extensively in Chapter 13. Note, however, that this
model can also be used for any other loan portfolios provided by the user. Please read
GettingStarted.pdf in the applications folder after installation for more instructions.

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